KTH Royal Institute of Technology in Stockholm, Sweden, invites applications for a doctoral student position in AI-native Edge Computing for 6G. This research project is situated within the third-cycle subject of computer science and aims to design next-generation edge computing systems that are deeply integrated with future 6G wireless networks. The project will address the challenges of delivering massive improvements in speed, responsiveness, and energy efficiency by developing smart, distributed computing architectures built directly into the network infrastructure.

Research will focus on combining heterogeneous computing platforms with distributed MIMO architectures to support both real-time AI workloads and traditional signal processing. The overarching goal is to create intelligent, scalable, and sustainable network nodes capable of handling a wide range of tasks, from user services to advanced coordination. A significant emphasis will be placed on the development of optimization algorithms that incorporate machine learning components, with opportunities for collaboration with industrial partners such as Ericsson, Atlas Copco, and Telenor, as well as the TECoSA competence center at KTH.

The Division of Network and Systems Engineering at KTH conducts fundamental research in networked systems, wireless communications, and cyber security. The research environment is highly collaborative, with connections to leading academic institutions including MIT, UIUC, and EPFL. The position is part of major research initiatives such as the Wallenberg AI, Autonomous Systems and Software Program and Digital Futures, providing a vibrant and innovative setting for doctoral studies.

Supervision will be provided by Professors György Dán, Emil Björnson, and Cicek Cavdar, offering expertise in networked systems, wireless communications, and optimization. The position is full-time, temporary, and funded with a monthly salary according to KTH's doctoral student salary agreement, including employee benefits. The employment period is up to four years, with possible renewals as per KTH regulations.

Eligibility requirements include a second cycle degree (e.g., master's) or equivalent, with at least 240 higher education credits (60 at the second-cycle level), and English proficiency equivalent to English B/6. Selection criteria emphasize academic excellence, relevant coursework, personal skills, and specialization in optimization, mathematical statistics, or machine learning. Applicants should be goal-oriented, able to work independently and collaboratively, and possess strong analytical abilities.

Applications must be submitted via KTH's recruitment system by January 11, 2026. Required documents include a CV, diplomas, grades, language certificates, certified translations if applicable, and representative publications or technical reports. KTH is committed to equality, diversity, and providing a creative and dynamic environment for growth and development. For further information, contact Professor György Dán at [email protected].

Join KTH and contribute to shaping the future of wireless infrastructure and AI-driven edge computing in a leading international technical university.